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@mrahul17
Created March 14, 2015 08:49
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Tardis data set
>>> lines_data[0]
(8, 66.772, 14, 5, 0.027030168289315495, 0.04054525243397324, 0.0, 36.0, 4.489792997064637e+16, 45453772.17738786, 30302514.784925245, 40439167617.50947)
>>> lines_data[0]
(8, 66.772, 14, 5, 0.027030168289315495, 0.04054525243397324, 0.0, 36.0, 4.489792997064637e+16, 45453772.17738786, 30302514.784925245, 40439167617.50947)
>>> lines_data[1]
(10, 69.204, 14, 5, 0.0866842126131329, 0.0866842126131329, 0.0, 35.0, 4.332010548523206e+16, 100717918.92086083, 100717918.92086083, 120731290053.8376)
>>> lines_data[2]
(11, 69.236, 14, 5, 0.06192253818286209, 0.09288380727429314, 0.0, 34.0, 4.330008348258131e+16, 107971097.37718476, 71980731.58478984, 86164235409.22531)
>>> lines_data[3]
(12, 69.448, 14, 5, 0.01769864460960345, 0.0353972892192069, 1.0, 35.0, 4.316790375532773e+16, 41272928.49085178, 20636464.24542589, 24477257110.58792)
>>> levels_data[0]
(14, 0, 0, 0.0, 1, True)
>>> levels_data[1]
(14, 0, 1, 0.0095610410439075, 3, True)
>>> levels_data[2]
(14, 0, 2, 0.02766794055936285, 5, True)
>>> levels_data[3]
(14, 0, 3, 0.780957834136248, 5, False)
>>>
@wkerzendorf
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look at the table, it's a pandas Dataframe and has additional metadata, like column names (I always suggest using ipython as this makes things much easier).

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